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Issue No.06 - Nov.-Dec. (2013 vol.33)
pp: 70-81
Xiaoguang Han , City Univ. of Hong Kong, Hong Kong, China
Hongbo Fu , City Univ. of Hong Kong, Hong Kong, China
Hanlin Zheng , Zhejiang Univ., Hangzhou, China
Ligang Liu , Univ. of Sci. & Technol. of China, Hefei, China
Jue Wang , Adobe Res., China
ABSTRACT
Stop-motion is a well-established animation technique but is often laborious and requires craft skills. A new video-based system can animate the vast majority of everyday objects in stop-motion style, more flexibly and intuitively. Animators can perform and capture motions continuously instead of breaking them into increments and shooting one still picture per increment. More important, the system permits direct hand manipulation without resorting to rigs, achieving more natural object control for beginners. The system's key component is two-phase keyframe-based capturing and processing, assisted by computer vision techniques. With this system, even amateurs can generate high-quality stop-motion animations.
INDEX TERMS
Animation, Motion control, Video communication, Computer vision, User interfaces,computer graphics, stop-motion, animation, user interface, computer vision, keyframes
CITATION
Xiaoguang Han, Hongbo Fu, Hanlin Zheng, Ligang Liu, Jue Wang, "A Video-Based System for Hand-Driven Stop-Motion Animation", IEEE Computer Graphics and Applications, vol.33, no. 6, pp. 70-81, Nov.-Dec. 2013, doi:10.1109/MCG.2013.40
REFERENCES
1. S. Zhai, “Human Performance in Six Degree of Freedom Input Control,” PhD dissertation, Graduate Dept. of Industrial Eng., Univ. of Toronto, 1995.
2. C. Liu, “Beyond Pixels: Exploring New Representations and Applications for Motion Analysis,” PhD dissertation, Dept. of Electrical Eng. and Computer Science, MIT, 2009.
3. B.T. Truong and S. Venkatesh, “Video Abstraction: A Systematic Review and Classification,” ACM Trans. Multimedia Computing, Communications, and Applications, vol. 3, no. 1, 2007, article 3.
4. Y. Boykov and O. Veksler, “Graph Cuts in Vision and Graphics: Theories and Applications,” Handbook of Mathematical Models in Computer Vision, N. Paragios, Y. Chen, and O. Faugeras eds., Springer, 2006, chapter 5.
5. P. Pérez, M. Gangnet, and A. Blake, “Poisson Image Editing,” ACM Trans. Graphics, vol. 22, no. 3, 2003, pp. 313-318.
6. P. Sand and S. Teller, “Video Matching,” ACM Trans. Graphics, vol. 23, no. 3, 2004, pp. 592-599.
7. Q.-X. Huang, R. Mech, and N. Carr, “Optimizing Structure Preserving Embedded Deformation for Resizing Images and Vector Art,” Computer Graphics Forum, vol. 28, no. 7, 2009, pp. 1887-1896.
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